The invention relates to a method of data reduction of a luminance and/or chrominance signal of a digital picture signal by means of fractal image coding, in which method each image of the luminance/chrominance signal is divided into range blocks of n.times.n pixels each, in which a domain block is searched for each range block, which domain block is imageable on the range block with a minimal deviation while using a transformation function, which domain blocks have a larger size than the range blocks, and in which information on the transformation functions is transmitted, from which information the image data are regained at the receiver end in an iterative process. The invention also relates to arrangements for performing the method.
A method of data reduction of a picture signal or of components of a picture signal by means of fractal image coding, in which an image is divided into range blocks and domain blocks, is known from "Image Coding Based on a Fractal Theory of Iterated Contractive Image Transformation, Arnaud E. Jacquin, IEEE Transactions on Image Processing, Vol. 1 (1), pp. 18 to 30, January 1992. According to Jacquin, an image of a picture signal is split up into what are called range blocks. Each range block is assigned a function, which should have the property of contractivity, and images an arbitrary block, referred to as domain block, on the range block. These functions of all range blocks of an image jointly constitute a function system which is also referred to as iterated function system.
At the encoder end, this method presents the problem that a domain block must be found for each range block, which domain block should be imageable on the range block with minimal errors while using the transformations found. To this end, all domain blocks in question must be examined on these criteria. It should be noted that the domain blocks may fundamentally be arranged arbitrarily in the image. Thus, for example, a block of 2n.times.2n pixels should not only be examined on its original location, but also, for example, rotated 90.degree., 180.degree. and 270.degree. in different directions. The process of searching an appropriate domain block for each range block in an image is thus very elaborate.
A search method, in which also each domain block which is possible in the image is examined for each range block and the optimum imaging prescription is computed for each of these pairs, is known from "Fractal Image Compression", M. F. Barnsley, L. B. Hurd, Academic Press Professional 1993. However, this is an elaborate process. In an image with nxn pixels, the search process is of the order of o(n.sup.2).
A search method, in which the domain blocks are grouped in different classes and only the domain blocks of the appropriate classes are searched for a matching range block, is known from "A Theory of Iterated Markov Operators with Applications to Digital Image Processing" by A. E. Jacquin, PhD Thesis, Georgia Institute of Technology, USA, 1989. This method operates more rapidly than Barnsley's method, but the computation complexity further remains of the order of o=n.sup.2.